Explore Workflows

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Graph Name Retrieved From View
workflow graph Generate genome index STAR RNA

Workflow makes indices for [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886). It performs the following steps: 1. Runs `STAR --runMode genomeGenerate` to generate indices, based on [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) and [GTF](http://mblab.wustl.edu/GTF2.html) input files, returns results as an array of files 2. Transforms array of files into [Direcotry](http://www.commonwl.org/v1.0/CommandLineTool.html#Directory) data type 3. Separates *chrNameLength.txt* file as an output

https://github.com/datirium/workflows.git

Path: workflows/star-index.cwl

Branch/Commit ID: d6f58c383d0676269afb519399061191a1144a6a

workflow graph Motif Finding with HOMER with random background regions

Motif Finding with HOMER with random background regions --------------------------------------------------- HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. Here is how we generate background for Motifs Analysis ------------------------------------- 1. Take input file with regions in a form of “chr\" “start\" “end\" 2. Sort and remove duplicates from this regions file 3. Extend each region in 20Kb into both directions 4. Merge all overlapped extended regions 5. Subtract not extended regions from the extended ones 6. Randomly distribute not extended regions within the regions that we got as a result of the previous step 7. Get fasta file from these randomly distributed regions (from the previous step). Use it as background For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/)

https://github.com/datirium/workflows.git

Path: workflows/homer-motif-analysis.cwl

Branch/Commit ID: 7ced5a5259dbd8b3fc64456beaeffd44f4a24081

workflow graph steplevel-resreq.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/steplevel-resreq.cwl

Branch/Commit ID: c7c97715b400ff2194aa29fc211d3401cea3a9bf

workflow graph count-lines7-wf.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/count-lines7-wf.cwl

Branch/Commit ID: 1f3ef888d9ef2306c828065c460c1800604f0de4

workflow graph Per-chromosome pindel

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/pindel_cat.cwl

Branch/Commit ID: c235dc6d623879a6c4f5fb307f545c9806eb2d23

workflow graph Workflow to run pVACseq from detect_variants and rnaseq pipeline outputs

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/pvacseq.cwl

Branch/Commit ID: a9133c999502acf94b433af8d39897e6c2cdf65f

workflow graph phase VCF

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/phase_vcf.cwl

Branch/Commit ID: a9133c999502acf94b433af8d39897e6c2cdf65f

workflow graph RNA-Seq alignment and transcript/gene abundance workflow

https://github.com/genome/analysis-workflows.git

Path: definitions/pipelines/rnaseq.cwl

Branch/Commit ID: a9133c999502acf94b433af8d39897e6c2cdf65f

workflow graph align_sort_sa

https://github.com/ncbi/pgap.git

Path: task_types/tt_align_sort_sa.cwl

Branch/Commit ID: 89098668413e90519c99b35143bffec509d3599c

workflow graph bulk scRNA-seq pipeline using Salmon

https://github.com/hubmapconsortium/salmon-rnaseq.git

Path: bulk-pipeline.cwl

Branch/Commit ID: a9022e73a8a0f01685b1241b87d5e793250845fd